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A morphological gradient approach to color edge detection

A morphological gradient approach to color edge detection
A morphological gradient approach to color edge detection
A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.
edge detection, gradient methods, image colour analysis, mathematical morphology
1057-7149
1454-1463
Evans, Adrian N
dfcf9756-8602-4a40-8905-663e300da7b4
Liu, Xin U
89b89a43-46f5-470c-9f82-c5d5f59c12db
Evans, Adrian N
dfcf9756-8602-4a40-8905-663e300da7b4
Liu, Xin U
89b89a43-46f5-470c-9f82-c5d5f59c12db

Evans, Adrian N and Liu, Xin U (2006) A morphological gradient approach to color edge detection. IEEE Transactions on Image Processing, 15 (6), 1454-1463.

Record type: Article

Abstract

A new color edge detector based on vector differences is proposed. The basic technique gives as its output the maximum distance between the vectors within a mask. When applied to scalar-valued images, the method reduces to the classic morphological gradient. The technique is relatively computationally efficient and can also be readily applied to other vector-valued images. To improve the performance in the presence of noise, a novel pairwise outlier rejection scheme is employed. A quantitative evaluation using Pratt's figure of merit shows the new technique to outperform other recently proposed color edge detectors. In addition, application to real images demonstrates the approach to be highly effective despite its low complexity.

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More information

Published date: June 2006
Keywords: edge detection, gradient methods, image colour analysis, mathematical morphology
Organisations: Electronics & Computer Science

Identifiers

Local EPrints ID: 262811
URI: http://eprints.soton.ac.uk/id/eprint/262811
ISSN: 1057-7149
PURE UUID: 6839ddfb-c16c-4aae-a33e-9efdc7106b56

Catalogue record

Date deposited: 06 Jul 2006
Last modified: 14 Mar 2024 07:18

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Contributors

Author: Adrian N Evans
Author: Xin U Liu

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